0483250 20240103215158.020171214235959.9 85038001582 000424628300007 10.1016/j.patrec.2017.12.013 6 s. P cav_un_epca*02573890167-86551021 (2018)44-49Elsevier Rotation invariants Orthogonal polynomials Recurrent relation Hermite-like polynomials Hermite moments cav_un_auth*0236665 Yang B. CN cav_un_auth*0101087 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Flusser Jan UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0355333 Kautský J. AU http://library.utia.cas.cz/separaty/2017/ZOI/flusser-0483250.pdf cav_un_auth*0314467 GA15-16928S GA ČR Orientation-independent object recognition mostly relies on rotation invariants. Invariants from moments orthogonal on a square have favorable numerical properties but they are difficult to construct. The paper presents sufficient and necessary conditions, that must be fulfilled by 2D separable orthogonal polynomi- als, for being transformed under rotation in the same way as are the monomials. If these conditions have been met, the rotation property propagates from polynomials to moments and allows a straightforward derivation of rotation invariants. We show that only orthogonal polynomials belonging to a specific class exhibit this property. We call them Hermite-like polynomials. JD 20000 20200 20206 2019 3 4 A hod 4ah 20231122142906.5 RVO:67985556 http://hdl.handle.net/11104/0278695 1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS S 3+4 Article Computer Science Artificial Intelligence COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE 2.822 0.638 8.5 0.01309 0.731 12661 0.662 2.656 271 Q2 52.042 63.1 Q2 Q2 0.77 Q2 63.06 2018 Soubory v repozitáři: flusser-0483250.pdf 85038001582 SCOPUS PUBMED 000424628300007 WOS cav_un_epca*0257389 Pattern Recognition Letters 0167-8655 1872-7344 Roč. 102 č. 1 2018 44 49 Elsevier